rasterbaserade

Rasterbaserade (from Swedish raster-based) describes systems, images and data models that represent information as a regular grid of discrete cells or pixels. Each cell stores a value or set of values that represent properties at that location, such as color, elevation, temperature, or reflectance. Raster-based approaches contrast with vector models, which represent features using points, lines and polygons.

Raster data are common in digital photography, remote sensing, geographic information systems (GIS), scientific imaging and computer graphics. Typical raster file formats include TIFF, JPEG, PNG and GeoTIFF (for georeferenced spatial data). Important characteristics are spatial resolution (cell size), bit depth (value precision), number of bands (channels) and coordinate reference for spatial rasters.

Advantages of raster-based representations include simplicity of analysis, natural fit for continuous phenomena and efficiency for pixel-wise operations such as filtering, convolution, classification and map algebra. Limitations include large storage requirements for high resolution data, loss of precision when scaling, and less efficient representation of discrete linear or cadastral features compared with vector formats.

Processing workflows for raster-based data include resampling, reprojection, compression, segmentation and change detection. In GIS and remote sensing, raster analysis is used for terrain modeling, land cover mapping and environmental monitoring. In digital imaging and printing, raster techniques govern color representation, halftoning and rasterization of vector content for output devices. Interoperability efforts focus on standardized formats and metadata to preserve spatial reference and provenance.